Five weeks ago I launched a new website, with a few friends, including Miro Dudik and David Pennock, called Microsoft Prediction Lab. The website consolidates research into both non-representative polling and prediction games. I have spent years understanding how various raw data: polling, prediction markets, and social media and online data, can be transformed into indicators of present interest and sentiment, as well as predictions, of varying populations. Then, how decision makers allocate resources with the low latency and quantifiable market intelligence that we produce. Microsoft Prediction Lab allows us to continuously innovate not only on the path of raw data to analytics to consumption, but the collection of the data itself. Please take a look at this post on the mission of Microsoft Prediction Lab.

First, we would like the thank the thousands of active users who made this first game such an interesting and meanignful experience!

Microsoft Prediction Lab has a market for all 507 elections in the midterms: 36 senatorial, 36 gubernatorial, and 435 house. In each of these markets users can buy and sell contracts on the possible outcomes of each election. For example, in New Hampshire there are two possible outcomes: Democratic candidate Jeanne Shaheen and Republican candidate Scott Brown. A prediction on Shaheen would return 112 points for every 100 wagered, while a prediction on Brown would return 467 point for the same 100 points! If someone thought that Brown as undervalued, that there was a good return in wagering 100 points for 467, s/he should predict Brown and if s/he thought Shaheen was undervalued they should buy Shaheen. As people predict Brown, the return goes down and vice-versa.

The return that an investment settles on in a market is extremely correlated with the probability of the outcome. We show the translation of the price to the probability on the market alongside the return on prediction.

Further, the markets moved quite a bit over the last few weeks. Actually, there was movement in most of the 507 markets. In this market 85 people placed predictions, while others saw well into triple digits. To test how efficient that movement was, whether the crowd was supplying information, we captured the probabilities in all 507 races at about midnight on Election Eve.

These probabilities represent the probability of victory for the party just before 12:00 AM on Election Day. We look forward to checking back later this week to see how Microsoft Prediction Lab did … and, for those of you playing the game, you have until 9 PM ET to keep the predictions coming!